FUZZY-GA PID CONTROLLER WITH INCOMPLETE DERIVATION AND ITS APPLICATION TO INTELLIGENT BIONIC ARTIFICIAL LEGS

以模糊推理和遗传算法为基础，提出了一种新的具有不完全微分的最优PID控制器的设计方法，该控制器由离线和在线两部分组成，在离线部分，以系统响应的超调量、上升时间以及调整时间为性能指标，利用遗传算法搜索出一组最优的PID参数Kp^*、Ti^*和Td^*，作为在线部分调整的初始值，在在线部分，一个专用的PID参数优化程序以离线部分获得Kp^*、Ti^*和Td^*为基础，根据系统当前的误差e和误差变化率e^.，通过一个模糊推理系统在线调整系统瞬态响应的PID参数，以确保系统的响应具有最优的动态和稳态性能．该控制器已被用来控制由作者设计的智能仿生人工腿中的执行电机．计算机仿真结果表明，该控制器具有良好的控制性能和鲁棒性能

Servo control system for intelligent artificial legs based on DSP chip and fuzzy PD control strategy

智能人工腿最显著的特点是能模仿人体健康腿的运动方式且步行速度可自然、随意地跟随截肢者步行速度的变化而变化 .对其进行研究对改善残疾人的生存条件和促进医疗事业的发展具有重要的现实意义 .以前研制的智能人工腿 ,其汽缸内针阀开度的控制都是采用步进电机所构成的开环系统 ,位置精度不高 ,为此 ,作者针对智能人工腿的控制原理和TMS3 2 0F2 4 0数字信号处理器的主要特点 ,设计了 1种基于TMS3 2 0F2 4 0的直流电机模糊位置伺服控制系统的结构 ,并对该位置伺服系统进行了计算机仿真 .实验结果表明 ,所设计的伺服控制系统具有智能性、鲁棒性、快速性和准确性 ,可以有效地用于智能人工腿的行..

工业机器人时间最优轨迹规划及轨迹控制的理论与实验研究

A new method used for time-optimal trajectory planning and control of industrial robots is proposed, which can ensure the motion of a robot&#39;s hand along a specified path in Cartesian space has the minimum traveling time under the constraints on the boundary values of joint displacements, velocities, accelerations, and jerks. In this method, the planned joint trajectories are all expressed by a quadratic polynomial plus a cosinoidal function and are continuous not only in displacements, velocities, accelerations but also in jerks. By using the method, a robot&#39;s working efficiency can be raised and its life span can be extended. The results of computer simulation and experiment with a Unimate PUMA 560 type robot proves that this method is correct and effective. It provides a better solution to the problem of industrial robot&#39;s time-optimal trajectory planning and control under the nonlinear kinematical constraints. <br type="_moz" /

On-line computational scheme for dynamic walking of anthropomorphic biped robots

Based on the Luh-Walker-Paul&#39;s algorithm, a new and more effective on-line computational scheme used for real-time control of dynamic walking of anthropomorphic biped robots is developed. This scheme includes two algorithms, one is the famous Luh-Walker-Paul&#39;s algorithm used for the single-foot supporting phase, and another is called IDADFS algorithm which is developed in this paper and used for the double-feet supporting phase. In IDADFS algorithm, the authors not only have given the recursive formulas for the kinematic and dynamic computations but also have proposed three criteria to examine the correctness of these computations. By means of this new computational scheme, one can perform precise real-time control for the dynamic walking of anthropomorphic biped robots. It should be pointed out that the research result of this paper can be also spread to multilegged robots. The more important is that the IDADFS algorithm also can be generalized to the manipulators with an open kinematic chain to realize the real-time control over this kind of manipulators when they execute closed-chain operating tasks or multirobots coordinative manipulations

Real-time accurate hand path tracking and joint trajectory planning for industrial robots(I)

Previously, researchers raised the accuracy for a robot&prime;s hand to track a specified path in Car tesian space mainly through increasing the number of knots on the path and the number of the path&prime;s segments, which results in the heavier online computational burden for the robot controller. Aiming at overcoming this drawback, the authors propose a new kind of real time accurate hand path tracking and joint trajectory planning method. Through selecting some extra knots on the specified hand path by a certain rule and introducing a sinusoidal function to the joint displacement equation of each segment, this method can greatly raise the path tracking accuracy of robot&prime;s hand and does not change the number of the path&prime;s segments. It also does not increase markedly the computational burden of robot controller. The result of simulation indicates that this method is very effective, and has important value in increasing the application of industrial robots